Software Engineer Intern, Undergraduate - Summer 2027 (Mountain View, CA)

LinkedIn is the worlds largest professional network, built to create economic opportunity for every member of the global workforce. Our products help people make powerful connections, discover exciting opportunities, build necessary skills, and gain valuable insights every day. Were also committed to providing transformational opportunities for our own employees by investing in their growth. We aspire to create a culture thats built on trust, care, inclusion, and fun where everyone can succeed. This internship role will be based out of Headquarters in Mountain View, California.At LinkedIn, our approach to flexible work is centered on trust and optimized for culture, connection, clarity, and the evolving needs of our business. The work location of this role is hybrid, meaning it will be performed both from home and from a LinkedIn office on select days, as determined by the business needs of the team. LinkedIn is looking for Undergraduate Software Engineering Interns to learn, grow, and work with some of the brightest technical talent. As the engineering landscape evolves, we are developing the next generation of technical talent with strong computer science fundamentals, and the engineering judgment to build impactful products and platforms. Interns may work on advanced information-retrieval algorithms, massive-scale infrastructure and storage solutions, and large-scale applications for users across web and mobile devices. You may contribute to data-heavy platforms and applications, including next-generation data infrastructure for storage, streams, media, and analytics. You will help scale LinkedIn infrastructure to support massive data growth across the LinkedIn ecosystem and work with distributed systems, algorithms, caching, queuing, and distributed data storage. You may also use modern AI-powered development tools and emerging technologies to accelerate experimentation, debugging, and technical problem-solving while applying engineering judgment to validate and improve solutions. This internship offers the opportunity to strengthen systems-oriented skills, including multithreading, concurrency, scalability, and performance, and to work on cutting-edge open-source systems. You will collaborate with engineers, receive feedback, and participate in LinkedIn’s broader intern community while exploring how AI and emerging technologies are changing software development. Candidates must be enrolled in an undergraduate degree program and have an expected graduation date of December 2027 or later. Our internships are 12 weeks in length and will have the option of two intern sessions: May 24th, 2027 - August 13th, 2027 June 14th, 2027 - September 3rd, 2027 Responsibilities Scale distributed applications and make architectural tradeoffs using synchronous and asynchronous design patterns. Write code that delivers speed and quality. Apply AI-powered development tools where appropriate to accelerate experimentation and implementation while maintaining engineering rigor. Develop multi-tier, scalable, high-volume, high-performance, and reliable user-centric applications that operate 24x7. Produce high-quality software with unit-tested, code-reviewed work checked regularly for continuous integration. Evaluate technical solutions, test assumptions, and apply engineering judgement to validate and improve solutions before integration. Apply strong computer science fundamentals and engineering judgment to complex, real-world challenges at scale. Partner with engineers, mentors, and cross-functional teammates to exchange feedback and deepen technical skills. Basic Qualifications Pursuing a B.A. or B.S. degree in Computer Science or a related technical field and returning to the program after completion of the internship. Programming experience in Java, C, C++, C#, Python, Rust, Ruby, or a similar object-oriented programming language. Knowledge of core computer science concepts, object-oriented design, algorithm design, data structures, problem-solving, and complexity analysis. Preferred Qualifications Experience working in a short-cycle, agile, and iterative development team. Strong competencies in data structures, algorithms, software design, and object-oriented programming. Experience building, testing, debugging, or scaling software applications or systems through coursework, internships, research, hackathons, open-source contributions, or personal projects. Suggested Skills Distributed Systems Operating Systems Cloud Computing Software Engineering Data Structures and Algorithms Technical Problem-Solving As part of the application process for this role, after an initial qualifications review, candidates are required to successfully complete the HackerRank online code challenge. Instructions for completion of the code challenge will be sent to you if your application is selected to move forward in the process. LinkedIn is committed to fair and equitable compensation practices. The pay range for this role is $45 to $55. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to skill set, depth of experience, certifications, and specific work location. This may be different in other locations due to differences in the cost of labor. The total compensation package for this position may also include annual performance bonus, stock, benefits and/or other applicable incentive compensation plans. For more information, visit Equal Opportunity Statement We seek candidates with a wide range of perspectives and backgrounds and we are proud to be an equal opportunity employer. LinkedIn considers qualified applicants without regard to race, color, religion, creed, gender, national origin, age, disability, veteran status, marital status, pregnancy, sex, gender expression or identity, sexual orientation, citizenship, or any other legally protected class. LinkedIn is committed to offering an inclusive and accessible experience for all job seekers, including individuals with disabilities. Our goal is to foster an inclusive and accessible workplace where everyone has the opportunity to be successful. 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